A new CNBP paper “Statistically strong label-free quantitative identification of native fluorophores in a biological sample,” by Saabah B. Mahbub (first author pictured), Martin Plöschner, Martin E. Gosnell, Ayad G. Anwer and Ewa M. Goldys has just been published in Scientific Reports and is available online.
This work addresses a genuine shortage of methods for real-time continuous monitoring of biochemistry of cells and tissues, especially live cells. Saabah Mahbub and team developed an automated and unbiased unmixing methodology to non-invasively detect the presence and spatial distributions of endogenous fluorophores in retina cells. The method was validated on artificial images, where the addition of a varying known level of noise has allowed to quantify the accuracy of spectral unmixing.
With its capability for high throughput, automation and embedded compatibility with statistical analysis this work will contribute to improved quantification and objectivity in biomedical research.